Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
LLM-based Skill Diffusion for Zero-shot Policy Adaptation
Authors: Woo Kyung Kim, Youngseok Lee, Jooyoung Kim, Honguk Woo
NeurIPS 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Through experiments, we demonstrate the zero-shot adaptability of LDu S to various context types including different specification levels, multi-modality, and varied temporal conditions for several robotic manipulation tasks, outperforming other language-conditioned imitation and planning methods. |
| Researcher Affiliation | Academia | Woo Kyung Kim1, Youngseok Lee2, Jooyoung Kim1, Honguk Woo1 1 Department of Computer Science and Engineering, Sunkyunkwan University 2 Department of Electrical and Computer Engineering, Sungkyunkwan University EMAIL |
| Pseudocode | Yes | Algorithm 1 Policy adaptation via LLM-guided diffusion |
| Open Source Code | Yes | We submit the code and shows the details of our implementations in Appendix B. |
| Open Datasets | Yes | We use the Meta World benchmark [39], specifically with 10 different robot manipulation goals. |
| Dataset Splits | No | For data collection, we emulate rule-based expert policies. For each goal, we collect 60 trajectories, varying the speed of the agent as well as the position and weight of the objects being manipulated. |
| Hardware Specification | Yes | All experiments are conduced on a system equipped with an Intel(R) Core(TM) i9-10980XE CPU and an NVIDIA RTX A6000 GPU. |
| Software Dependencies | No | We implement LCD [3] using the open source projects Jax 3 and Haiku 4. |
| Experiment Setup | Yes | The hyperparameter settings for LDu S are summarized in Table 10. |